mlsanityData to 7 Oct 2026

Lecture Notes on Randomized Linear Algebra

arXiv 1608.04481 ↗First posted 16 Aug 2016cs.DS stat.MLcited by 11

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Abstract (arXiv)

These are lecture notes that are based on the lectures from a class I taught on the topic of Randomized Linear Algebra (RLA) at UC Berkeley during the Fall 2013 semester.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Aug 2016.

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Citing papers per year: 2021: 3; 2022: 1; 2023: 3; 2024: 3; 2025: 1.

11 papers.

  1. 2023Matrix Compression via Randomized Low Rank and Low Precision Factorizationcited by 25
  2. 2024Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learningcited by 11
  3. 2024Efficient Sketches for Training Data Attribution and Studying the Loss Landscapecited by 10
  4. 2025GraSS: Scalable Data Attribution with Gradient Sparsification and Sparse Projectioncited by 8
  5. 2022Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration and Lower Boundscited by 5
  6. 2024Randomized Algorithms for Symmetric Nonnegative Matrix Factorizationcited by 3
  7. 2021Quantum Machine Learning For Classical Datacited by 2
  8. 2023Gradient Coding with Iterative Block Leverage Score Samplingcited by 2
  9. 2021Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputerscited by 1
  10. 2021Oversampling Divide-and-conquer for Response-skewed Kernel Ridge Regressioncited by 0
  11. 2023Iterative Sketching for Secure Coded Regressioncited by 0